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503425825 MDU6SXNzdWU1MDM0MjU4MjU= 3376 .coarsen() method for the xarray.Dataset removes its attributes. jejjohnson 3642622 closed 0     4 2019-10-07T12:39:14Z 2020-03-02T23:02:55Z 2020-03-02T23:02:55Z NONE      

Hello,

I am not sure if this is a bug or a feature but when one calls the xarray.coarsen() on a dataset, then the attributes get removed.

Dataset Example ```python import xarray as xr import numpy as np

var1 = np.linspace(10, 15, 100) var2 = np.linspace(5, 10, 100) coords = np.linspace(1, 10, 100)

dat = xr.Dataset( data_vars={'var1': ('coord', var1), 'var2': ('coord', var2)}, coords={'coord': coords} ) dat.attrs['model_id'] = 'model1'

coarsen dataset

dat = dat.coarsen(coord=5).mean()

print dataset

dat ```

Actual Output

python <xarray.Dataset> Dimensions: (coord: 20) Coordinates: * coord (coord) float64 1.182 1.636 2.091 2.545 ... 8.455 8.909 9.364 9.818 Data variables: var1 (coord) float64 10.1 10.35 10.61 10.86 ... 14.14 14.39 14.65 14.9 var2 (coord) float64 5.101 5.354 5.606 5.859 ... 9.141 9.394 9.646 9.899

Expected Output

python <xarray.Dataset> Dimensions: (coord: 20) Coordinates: * coord (coord) float64 1.182 1.636 2.091 2.545 ... 8.455 8.909 9.364 9.818 Data variables: var1 (coord) float64 10.1 10.35 10.61 10.86 ... 14.14 14.39 14.65 14.9 var2 (coord) float64 5.101 5.354 5.606 5.859 ... 9.141 9.394 9.646 9.899 Attributes: model_id: 1

Problem Description

I believe the attributes should stay within the xarray.Dataset no matter what the operations that are done on it. Obviously maybe for some operations an entry like model_id could change because it's no longer the model. But I believe that should be left up to the user. Perhaps a warning in the docs might be sufficient. The behaviour isn't consistent with the xarray.coarsen() function on the xarray.DataArray example where the attributes remain the same (see details below).

DataArray Example

```python data = np.random.rand(50, 3) locs = ['IA', 'IL', 'IN'] times = pd.date_range('2000-01-01', periods=50) foo = xr.DataArray(data, coords=[times, locs], dims=['time', 'space']) foo.attrs['data_id'] = 'data1' foo ``` #### Expected/Actual Output ```python <xarray.DataArray (time: 10, space: 3)> array([[0.3537571 , 0.50698482, 0.35923528], [0.62127828, 0.41852822, 0.5617278 ], [0.38669858, 0.60446037, 0.45699182], [0.41538186, 0.81251298, 0.3919821 ], [0.67914214, 0.45866817, 0.58625095], [0.63560785, 0.53796635, 0.48231731], [0.60802724, 0.54003065, 0.38456255], [0.46492592, 0.78542293, 0.50788668], [0.53757801, 0.56765902, 0.52288412], [0.51085502, 0.51448292, 0.67426125]]) Coordinates: * time (time) datetime64[ns] 2000-01-03 2000-01-08 ... 2000-02-17 * space (space) <U2 'IA' 'IL' 'IN' Attributes: data_id: data1 ``` </details>

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.4 (default, Aug 13 2019, 20:35:49) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 3.10.0-327.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: None.None libhdf5: 1.10.4 libnetcdf: 4.6.1 xarray: 0.13.0 pandas: 0.25.1 numpy: 1.17.2 scipy: 1.3.1 netCDF4: 1.4.2 pydap: None h5netcdf: None h5py: 2.9.0 Nio: None zarr: 2.3.2 cftime: 1.0.3.4 nc_time_axis: None PseudoNetCDF: None rasterio: 1.0.21 cfgrib: None iris: None bottleneck: None dask: 2.4.0 distributed: None matplotlib: 3.1.1 cartopy: 0.17.0 seaborn: None numbagg: None setuptools: 41.2.0 pip: 19.2.3 conda: None pytest: None IPython: 7.8.0 sphinx: None 
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   completed xarray 13221727 issue

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